Most “personal AI assistant” products work by shipping your most personal data, your health, your calendar, your inbox, to someone else’s servers. ElliotOS is a small experiment in doing the opposite: a daily-brief assistant that reads your real life and runs the AI locally, so nothing leaves your machine unless you explicitly let it.
It’s a Wildlab project, and it’s public.
What it does
Twice a day it collects from eight-plus sources, Apple Health, macOS usage stats, Google Calendar, Gmail, Slack, nutrition, news, sport, processes them with a local model, and posts a morning and an evening digest to Slack. The morning brief is a greeting, your calendar, a health and productivity check, headlines, and a focus for the day; the evening one is a reflection, a wellness check, and a preview of tomorrow.
The processing is done by a local Ollama model by default. Cloud models (OpenAI, Anthropic) are an opt-in fallback, not the path of least resistance. No tracking, credentials in environment variables, your data staying on your hardware.
Why a studio builds this
This is a personal tool, but it’s also us thinking out loud about something we do for clients: responsible AI deployment. When the data is sensitive, “just send it to a big model’s API” is a decision, not a default, and often the wrong one. Knowing when a task can run locally, when it needs a frontier model, and how to draw that line is part of the AI-governance work we bring to real projects.
The whole thing is on GitHub if you want to read how it’s wired together.
This is a Field Note from Wild Interactive, a design-led engineering studio in Wellington, NZ. Originally published at wildinteractive.co.nz/field-notes/a-local-first-personal-ai-that-never-phones-home.
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